As the open reading frames of hepatitis B virus(HBV)genomes are overlapping,resistance mutations(MTs)in HBV polymerase may result in stop codon MTs in hepatitis B surface proteins,which are usually detected as a mixed...As the open reading frames of hepatitis B virus(HBV)genomes are overlapping,resistance mutations(MTs)in HBV polymerase may result in stop codon MTs in hepatitis B surface proteins,which are usually detected as a mixed population with wild-type(WT)HBV.The question was raised how the coexistence of nucleos(t)ide analogs(NAs)resistance MTs and WT sequences affects HBV replication.In the present study,HBV genomes with frequently detected reverse transcriptase(RT)/surface truncation MTs,rtA181T/sW172^*,rtV191I/sW182^*and rtM204I/sW196^*,were phenotypically characterized alone or together with their WT counterparts in different ratios by transient transfection in the absence or presence of Nas.In the absence of Nas,RT/surface truncation MTs impaired the expression and secretion of HBV surface proteins,and had a dose-dependent negative effect on WT HBV virion secretion.However,in the presence of Nas,coexistence of MTs with WT maintained viral replication,and the presence of WT was able to rescue the production of MT HBV virions.Our findings reveal that complementation of WT and MT HBV genomes is highly effective under drug treatment.展开更多
Deep coal-energy mining frequently results in microseismic(MS)events,which may be a precursor to the risk of rockbursts and pose risks to human safety and infrastructure.Therefore,quantitatively predicting the time,en...Deep coal-energy mining frequently results in microseismic(MS)events,which may be a precursor to the risk of rockbursts and pose risks to human safety and infrastructure.Therefore,quantitatively predicting the time,energy,and location(TEL)of future MS events is crucial for understanding and preventing potential catastrophic events.In this study,we introduced the application of spatiotemporal graph convolutional networks(STGCN)to predict the TEL of MS events induced by deep coal-energy mining.Notably,this was the first application of graph convolution networks(GCNs)in the spatiotemporal prediction of MS events.The adjacency matrices of the sensor networks were determined based on the distance between MS sensors,the sensor network graphs we constructed,and GCN was employed to extract the spatiotemporal details of the graphs.The model is simple and versatile.By testing the model with on-site MS monitoring data,our results demonstrated promising efficacy in predicting the TEL of MS events,with the cosine similarity(C)above 0.90 and the mean relative error(MRE)below 0.08.This is critical to improving the safety and operational efficiency of deep coal-energy mining.展开更多
Deep neural networks are known to be vulnerable to adversarial attacks.Unfortunately,the underlying mechanisms remain insufficiently understood,leading to empirical defenses that often fail against new attacks.In this...Deep neural networks are known to be vulnerable to adversarial attacks.Unfortunately,the underlying mechanisms remain insufficiently understood,leading to empirical defenses that often fail against new attacks.In this paper,we explain adversarial attacks from the perspective of robust features,and propose a novel Generative Adversarial Network(GAN)-based Robust Feature Disentanglement framework(GRFD)for adversarial defense.The core of GRFD is an adversarial disentanglement structure comprising a generator and a discriminator.For the generator,we introduce a novel Latent Variable Constrained Variational Auto-Encoder(LVCVAE),which enhances the typical beta-VAE with a constrained rectification module to enforce explicit clustering of latent variables.To supervise the disentanglement of robust features,we design a Robust Supervisory Model(RSM)as the discriminator,sharing architectural alignment with the target model.The key innovation of RSM is our proposed Feature Robustness Metric(FRM),which serves as part of the training loss and synthesizes the classification ability of features as well as their resistance to perturbations.Extensive experiments on three benchmark datasets demonstrate the superiority of GRFD:it achieves 93.69%adversarial accuracy on MNIST,77.21%on CIFAR10,and 58.91%on CIFAR100 with minimal degradation in clean accuracy.Codes are available at:(accessed on 23 July 2025).展开更多
This study seeks a routine to quantify spatial pattern of land cover changes in semiarid environment of China based on post-classification comparison method.The method consists of three major steps:(1)the image classi...This study seeks a routine to quantify spatial pattern of land cover changes in semiarid environment of China based on post-classification comparison method.The method consists of three major steps:(1)the image classification and unification of classified results based on two-level land cover classification themes,(2)the establishment of land cover change classes based on an unification land cover classification theme,(3)the reclassification and mapping of land cover change classes with three overall classes including no-change,gain and loss based on the unification land cover class.This method was applied to detect the spatial pattern of land cover changes in Yinchuan Plain,one of famous irrigation agricultural zones of the Yellow River,China.The results showed the land cover had undergone a remarkable change from 1991 to 2002 in the study area(the changed area was over 30%).Rapid increase of cropland(12.5%),built-up area(131.4%)and rapid decrease of bare ground(51.7%)were alarming.The spatial pattern of land cover changes showed clear regional difference in the study area and was clearly related to human activities or natural factors.Thus,it obtained a better understanding of the human impact on the fragile ecosystem of China’s semiarid environment.展开更多
Microseismic source location is crucial for the early warning of rockburst risks.However,the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy.Intelligent techni...Microseismic source location is crucial for the early warning of rockburst risks.However,the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy.Intelligent techniques,such as the full convolutional neural network(FCNN),can capture spatial information but struggle with complex microseismic sequence.Combining the FCNN with the long shortterm memory(LSTM)network enables better time-series signal classification by integrating multiscale information and is therefore suitable for waveform location.The LSTM-FCNN model does not require extensive data preprocessing and it simplifies the microseismic source location through feature extraction.In this study,we utilized the LSTM-FCNN as a regression learning model to locate the seismic focus.Initially,the method of short-time-average/long-time-average(STA/LTA)arrival time picking was employed to augment spatiotemporal information.Subsequently,oversampling the on-site data was performed to address the issue of data imbalance,and finally,the performance of LSTM-FCNN was tested.Meanwhile,we compared the LSTM-FCNN model with previous deep-learning models.Our results demonstrated remarkable location capabilities with a mean absolute error(MAE)of only 7.16 m.The model can realize swift training and high accuracy,thereby significantly improving risk warning of rockbursts.展开更多
Three small bandgap non-fullerene(SBG NFAs) acceptors,BDTI,BDTI-2 F and BDTI-4 F,based on a carbon-oxygen bridged central core and thieno[3,4-b]thiophene linker,end-capped with varied electronwithdrawing terminal grou...Three small bandgap non-fullerene(SBG NFAs) acceptors,BDTI,BDTI-2 F and BDTI-4 F,based on a carbon-oxygen bridged central core and thieno[3,4-b]thiophene linker,end-capped with varied electronwithdrawing terminal groups,were designed and synthesized.The acceptors exhibit strong absorption from 600 nm to 1000 nm.The optimal device incorporating designed NFA and PTB7-Th polymer donor achieves a power conversion efficiency of 9.11% with near 0 eV HOMO offset.The work presents a case study of efficient non-fullerene solar cells with small HOMO offsets,which is achieved by blending PTB7-Th with fine-tuned SBG acceptor.展开更多
A possible explanation for ocean acidification-induced changes in fish behavior is a systemic effect on the nervous system.Three biological barriers at the blood–brain interface effectively separate the brain from th...A possible explanation for ocean acidification-induced changes in fish behavior is a systemic effect on the nervous system.Three biological barriers at the blood–brain interface effectively separate the brain from the body fluids.It is not known whether fish brain regions in contact with these barriers are affected by acidification.Here,we studied structural changes in medaka(Oryzias melastigma)brain regions contacting cerebrospinal fluid(CSF)after short-term(7 days)CO_(2) exposure.The brain water content decreased significantly and the superficial structure of the pia mater was changed,but there was no obvious damage to the internal structures of the brain after seawater acidification.Seawater acidification also led to an increase in apoptosis and a decrease in the number of proliferative cells in brain areas contacting CSF.These results indicate that the structure of CSF-contacting brain regions in medaka was affected by seawater acidification,and the brain responded to seawater acidification stress by increasing apoptosis and reducing proliferation.展开更多
Phenological models are valuable tools for predicting vegetation phenology and investigating the relationships between vegetation dynamics and climate. However, compared to temperate and boreal ecosystems, phenologica...Phenological models are valuable tools for predicting vegetation phenology and investigating the relationships between vegetation dynamics and climate. However, compared to temperate and boreal ecosystems, phenological modeling in alpine regions has received limited attention. In this study, we developed a semi-mechanistic phenological model, the Alpine Growing Season Index (AGSI), which incorporates the differential impacts of daily maximum and minimum air temperatures, as well as the constraints of precipitation and photoperiod, to predict foliar phenology in alpine grasslands on the Qinghai–Tibetan Plateau (QTP). The AGSI model is driven by daily minimum temperature (T_(min)), daily maximum temperature (T_(max)), precipitation averaged over the previous month (PA), and daily photoperiod (Photo). Based on the AGSI model, we further assessed the impacts of T_(min), T_(max), PA, and Photo on modeling accuracy, and identified the predominant climatic controls over foliar phenology across the entire QTP. Results showed that the AGSI model had higher accuracy than other GSI models. The total root mean square error (RMSE) of predicted leaf onset and offset dates, when evaluated using ground observations, was 12.9 ± 5.7 days, representing a reduction of 10.9%–54.1% compared to other models. The inclusion of T_(max) and PA in the AGSI model improved the total modeling accuracy of leaf onset and offset dates by 20.2%. Overall, PA and T_(min) showed more critical and extensive constraints on foliar phenology in alpine grasslands. The limiting effect of T_(max) was also considerable, particularly during July–November. This study provides a simple and effective tool for predicting foliar phenology in alpine grasslands and evaluating the climatic effects on vegetation phenological development in alpine regions.展开更多
The establishment of the National Key Ecological Function Areas(NKEFAs)is an important measure for national ecological security,but the current ecological and environmental evaluation of NKEFAs lacks research on the a...The establishment of the National Key Ecological Function Areas(NKEFAs)is an important measure for national ecological security,but the current ecological and environmental evaluation of NKEFAs lacks research on the air quality in the NKEFAs.This study presented the current status of the air quality in the NKEFAs and its driving factors using the geographic detector q-statistic method.The air quality in the NKEFAs was overall better than individual cities and urban agglomeration in eastern coast provinces of China,accounting for 9.21%of the days with air quality at Level III or above.The primary air pollutant was PM_(10),followed by PM_(2.5),with lower concentrations of the remaining pollutants.Pollution was more severe in the sand fixation areas,where air pollution was worst in spring and best in autumn,contrasting with other NKEFAs and individual cities and urban agglomerations.The main influencing factors of air quality index(AQI)in the NKEFAs were land use type,wind speed,and relative humidity also weighted more heavily than factors such as industrial pollution and anthropogenic emissions,and most of these influence factors have two types of interactive effects:binary and nonlinear enhancements.These results indicated that air pollution in the NKEFAs was not related with the emission by intensive economic development.Thus,the policies taking the NKEFAs as restricted development zones were effective,but the air pollution caused by PM_(10) also showed the ecological status in the NKEFAs,especially at sand fixation areas was not quite optimistic,and more strict environmental protection measures should be taken to improve the ecological status in these NKEFAs.展开更多
Activatable prodrugs have received considerable attention in cancer therapy due to their high specificity and reduced side effects.However,the theranostic prodrug with multiple cancerous organelles targeting and combi...Activatable prodrugs have received considerable attention in cancer therapy due to their high specificity and reduced side effects.However,the theranostic prodrug with multiple cancerous organelles targeting and combinational therapy is still rare.In this report,an esterase-responsive prodrug tetraphenylethylene functionalized quinolinium-ester-chlorambucil(TPEQC)was developed for dual organelles-targeted and image-guided cancer therapy through synergetic chemotherapy(CT)and photodynamic therapy(PDT).TPE-QC was constructed by conjugating an anticancer drug of chlorambucil with an aggregation-induced emission active photosensitizer of tetraphenylethylene functionalized hydroxyethyl quinolinium(TPE-QO)via the hydrolyzable ester linkage.The fluorescence and photosensitization of TPE-QC were initially quenched because of the photoinduced electron transfer(PET)effect.After reacting with esterase,the ester group of TPE-QC could be selectively hydrolyzed to release chlorambucil and TPE-QO,which terminated the PET process and switched on the fluorescence and photosensitization.Benefitting from the overexpressed esterase in cancer cells,TPE-QC could be efficiently activated in cancer cells rather than in normal cells,while the restoredfluorescence could preciselymonitor the release of TPE-QC.Importantly,activated TPE-QC accumulated in both organelles of lysosome and mitochondria,resulting in enhanced anticancer potency.In vivo experiments demonstrated that TPE-QC displayed efficient tumor microenvironment-activatable features and excellent tumor therapeutic effects through combinational CT and PDT.展开更多
Net area change analysis can dramatically underestimate total change of land cover, even sometimes seriously misinterpret ecological processes of the ecosystem, especially in arid or semiarid zones. In this paper, a s...Net area change analysis can dramatically underestimate total change of land cover, even sometimes seriously misinterpret ecological processes of the ecosystem, especially in arid or semiarid zones. In this paper, a suite of indices are presented to characterize land-cover swaps that may seriously damage the ecosystem in arid or semiarid zones, based on swap-change areas extracted from remotely sensed images. First, swap percentage of total area and swap intensity of total changes were used to determine the status of land-cover swap change in an area. Then, dominated swap category and individual swap- change intensity for a land-cover category were used to determine flagged land-cover swap-change categories. Finally, swap-change mode and Pielou＇s index were used to determine the land-cover swap-change processes of dominant categories. A case study is conducted using this approach, based on two land-cover maps in the 1980s and 2000 in Naiman Qi, Tongliao City, Inner Mongolia, China. This study shows that the approach can clearly quantify the severity and flagged classes of land-cover swap-change and reveal their relationship with ecological processes of the ecosystem. These results indicate that the approach can give deep insights into swap change, which can be very valuable to land-cover policy making and management.展开更多
基金supported by the Deutsche Forschungsgemeinschaft (TRR60)the National Nature Science Foundation of China (31770180, 31621061)+1 种基金the Youth Innovation Promotion Association CAS (No. 2016303)the Youth Planning Project of Hubei Health Planning Commission (WJ2017Q027)
文摘As the open reading frames of hepatitis B virus(HBV)genomes are overlapping,resistance mutations(MTs)in HBV polymerase may result in stop codon MTs in hepatitis B surface proteins,which are usually detected as a mixed population with wild-type(WT)HBV.The question was raised how the coexistence of nucleos(t)ide analogs(NAs)resistance MTs and WT sequences affects HBV replication.In the present study,HBV genomes with frequently detected reverse transcriptase(RT)/surface truncation MTs,rtA181T/sW172^*,rtV191I/sW182^*and rtM204I/sW196^*,were phenotypically characterized alone or together with their WT counterparts in different ratios by transient transfection in the absence or presence of Nas.In the absence of Nas,RT/surface truncation MTs impaired the expression and secretion of HBV surface proteins,and had a dose-dependent negative effect on WT HBV virion secretion.However,in the presence of Nas,coexistence of MTs with WT maintained viral replication,and the presence of WT was able to rescue the production of MT HBV virions.Our findings reveal that complementation of WT and MT HBV genomes is highly effective under drug treatment.
基金the financial support of the Key Technologies Research and Development Program(Grant No.2022YFC3003302)the National Natural Science Foundation of China(Grant Nos.51934007 and 52104230).
文摘Deep coal-energy mining frequently results in microseismic(MS)events,which may be a precursor to the risk of rockbursts and pose risks to human safety and infrastructure.Therefore,quantitatively predicting the time,energy,and location(TEL)of future MS events is crucial for understanding and preventing potential catastrophic events.In this study,we introduced the application of spatiotemporal graph convolutional networks(STGCN)to predict the TEL of MS events induced by deep coal-energy mining.Notably,this was the first application of graph convolution networks(GCNs)in the spatiotemporal prediction of MS events.The adjacency matrices of the sensor networks were determined based on the distance between MS sensors,the sensor network graphs we constructed,and GCN was employed to extract the spatiotemporal details of the graphs.The model is simple and versatile.By testing the model with on-site MS monitoring data,our results demonstrated promising efficacy in predicting the TEL of MS events,with the cosine similarity(C)above 0.90 and the mean relative error(MRE)below 0.08.This is critical to improving the safety and operational efficiency of deep coal-energy mining.
基金funded by the National Natural Science Foundation of China Project"Research on Intelligent Detection Techniques of Encrypted Malicious Traffic for Large-Scale Networks"(Grant No.62176264).
文摘Deep neural networks are known to be vulnerable to adversarial attacks.Unfortunately,the underlying mechanisms remain insufficiently understood,leading to empirical defenses that often fail against new attacks.In this paper,we explain adversarial attacks from the perspective of robust features,and propose a novel Generative Adversarial Network(GAN)-based Robust Feature Disentanglement framework(GRFD)for adversarial defense.The core of GRFD is an adversarial disentanglement structure comprising a generator and a discriminator.For the generator,we introduce a novel Latent Variable Constrained Variational Auto-Encoder(LVCVAE),which enhances the typical beta-VAE with a constrained rectification module to enforce explicit clustering of latent variables.To supervise the disentanglement of robust features,we design a Robust Supervisory Model(RSM)as the discriminator,sharing architectural alignment with the target model.The key innovation of RSM is our proposed Feature Robustness Metric(FRM),which serves as part of the training loss and synthesizes the classification ability of features as well as their resistance to perturbations.Extensive experiments on three benchmark datasets demonstrate the superiority of GRFD:it achieves 93.69%adversarial accuracy on MNIST,77.21%on CIFAR10,and 58.91%on CIFAR100 with minimal degradation in clean accuracy.Codes are available at:(accessed on 23 July 2025).
基金supported by National Key Basic Research and Development Program Grant(2006CB701305)Hong Kong Research Grants Council Competitive Earmarked Research Grant(HKBU 2029/07P)+1 种基金Hong Kong Baptist University Faculty Research Grant(FRG/06-07/II-76)China National Natural Science Foundation Grant(40101028)
文摘This study seeks a routine to quantify spatial pattern of land cover changes in semiarid environment of China based on post-classification comparison method.The method consists of three major steps:(1)the image classification and unification of classified results based on two-level land cover classification themes,(2)the establishment of land cover change classes based on an unification land cover classification theme,(3)the reclassification and mapping of land cover change classes with three overall classes including no-change,gain and loss based on the unification land cover class.This method was applied to detect the spatial pattern of land cover changes in Yinchuan Plain,one of famous irrigation agricultural zones of the Yellow River,China.The results showed the land cover had undergone a remarkable change from 1991 to 2002 in the study area(the changed area was over 30%).Rapid increase of cropland(12.5%),built-up area(131.4%)and rapid decrease of bare ground(51.7%)were alarming.The spatial pattern of land cover changes showed clear regional difference in the study area and was clearly related to human activities or natural factors.Thus,it obtained a better understanding of the human impact on the fragile ecosystem of China’s semiarid environment.
基金financial support of the Fundamental Research Funds for the Central Universities(Grant No.2022XSCX35)the National Natural Science Foundation of China(Grant Nos.51934007 and 52104230).
文摘Microseismic source location is crucial for the early warning of rockburst risks.However,the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy.Intelligent techniques,such as the full convolutional neural network(FCNN),can capture spatial information but struggle with complex microseismic sequence.Combining the FCNN with the long shortterm memory(LSTM)network enables better time-series signal classification by integrating multiscale information and is therefore suitable for waveform location.The LSTM-FCNN model does not require extensive data preprocessing and it simplifies the microseismic source location through feature extraction.In this study,we utilized the LSTM-FCNN as a regression learning model to locate the seismic focus.Initially,the method of short-time-average/long-time-average(STA/LTA)arrival time picking was employed to augment spatiotemporal information.Subsequently,oversampling the on-site data was performed to address the issue of data imbalance,and finally,the performance of LSTM-FCNN was tested.Meanwhile,we compared the LSTM-FCNN model with previous deep-learning models.Our results demonstrated remarkable location capabilities with a mean absolute error(MAE)of only 7.16 m.The model can realize swift training and high accuracy,thereby significantly improving risk warning of rockbursts.
基金the National Key R&D Program of China (2017YFA0204701)Strategic Priority Research Program of the Chinese Academy of Sciences (XDB12010200)+1 种基金National Basic Research Program of China (Program 973) (No. 2014CB643502)the National Natural Science Foundation of China (21572234, 21661132006, 91833304, 21402194) for their financial support。
文摘Three small bandgap non-fullerene(SBG NFAs) acceptors,BDTI,BDTI-2 F and BDTI-4 F,based on a carbon-oxygen bridged central core and thieno[3,4-b]thiophene linker,end-capped with varied electronwithdrawing terminal groups,were designed and synthesized.The acceptors exhibit strong absorption from 600 nm to 1000 nm.The optimal device incorporating designed NFA and PTB7-Th polymer donor achieves a power conversion efficiency of 9.11% with near 0 eV HOMO offset.The work presents a case study of efficient non-fullerene solar cells with small HOMO offsets,which is achieved by blending PTB7-Th with fine-tuned SBG acceptor.
基金supported by the National Key Research and Development Program of China,China(2018YFD0900902).
文摘A possible explanation for ocean acidification-induced changes in fish behavior is a systemic effect on the nervous system.Three biological barriers at the blood–brain interface effectively separate the brain from the body fluids.It is not known whether fish brain regions in contact with these barriers are affected by acidification.Here,we studied structural changes in medaka(Oryzias melastigma)brain regions contacting cerebrospinal fluid(CSF)after short-term(7 days)CO_(2) exposure.The brain water content decreased significantly and the superficial structure of the pia mater was changed,but there was no obvious damage to the internal structures of the brain after seawater acidification.Seawater acidification also led to an increase in apoptosis and a decrease in the number of proliferative cells in brain areas contacting CSF.These results indicate that the structure of CSF-contacting brain regions in medaka was affected by seawater acidification,and the brain responded to seawater acidification stress by increasing apoptosis and reducing proliferation.
基金jointly funded by the National Natural Science Foundation of China (42201059)the General Program of Guangdong Provincial Natural Science Foundation (2024A1515012731)the Science and Technology Program of Guangdong (2024B1212070012)。
文摘Phenological models are valuable tools for predicting vegetation phenology and investigating the relationships between vegetation dynamics and climate. However, compared to temperate and boreal ecosystems, phenological modeling in alpine regions has received limited attention. In this study, we developed a semi-mechanistic phenological model, the Alpine Growing Season Index (AGSI), which incorporates the differential impacts of daily maximum and minimum air temperatures, as well as the constraints of precipitation and photoperiod, to predict foliar phenology in alpine grasslands on the Qinghai–Tibetan Plateau (QTP). The AGSI model is driven by daily minimum temperature (T_(min)), daily maximum temperature (T_(max)), precipitation averaged over the previous month (PA), and daily photoperiod (Photo). Based on the AGSI model, we further assessed the impacts of T_(min), T_(max), PA, and Photo on modeling accuracy, and identified the predominant climatic controls over foliar phenology across the entire QTP. Results showed that the AGSI model had higher accuracy than other GSI models. The total root mean square error (RMSE) of predicted leaf onset and offset dates, when evaluated using ground observations, was 12.9 ± 5.7 days, representing a reduction of 10.9%–54.1% compared to other models. The inclusion of T_(max) and PA in the AGSI model improved the total modeling accuracy of leaf onset and offset dates by 20.2%. Overall, PA and T_(min) showed more critical and extensive constraints on foliar phenology in alpine grasslands. The limiting effect of T_(max) was also considerable, particularly during July–November. This study provides a simple and effective tool for predicting foliar phenology in alpine grasslands and evaluating the climatic effects on vegetation phenological development in alpine regions.
基金This work was supported by the National Key Research and Development Plan of China(Grant No.2016YFC0500205)the Research on Multi_Level Complex Spatial Data Model and the Consistency(No.41571391).
文摘The establishment of the National Key Ecological Function Areas(NKEFAs)is an important measure for national ecological security,but the current ecological and environmental evaluation of NKEFAs lacks research on the air quality in the NKEFAs.This study presented the current status of the air quality in the NKEFAs and its driving factors using the geographic detector q-statistic method.The air quality in the NKEFAs was overall better than individual cities and urban agglomeration in eastern coast provinces of China,accounting for 9.21%of the days with air quality at Level III or above.The primary air pollutant was PM_(10),followed by PM_(2.5),with lower concentrations of the remaining pollutants.Pollution was more severe in the sand fixation areas,where air pollution was worst in spring and best in autumn,contrasting with other NKEFAs and individual cities and urban agglomerations.The main influencing factors of air quality index(AQI)in the NKEFAs were land use type,wind speed,and relative humidity also weighted more heavily than factors such as industrial pollution and anthropogenic emissions,and most of these influence factors have two types of interactive effects:binary and nonlinear enhancements.These results indicated that air pollution in the NKEFAs was not related with the emission by intensive economic development.Thus,the policies taking the NKEFAs as restricted development zones were effective,but the air pollution caused by PM_(10) also showed the ecological status in the NKEFAs,especially at sand fixation areas was not quite optimistic,and more strict environmental protection measures should be taken to improve the ecological status in these NKEFAs.
基金supported by National Natural Science Foundation of China(nos.21975149,22077077 and 21672135)Funded Projects for the Academic Leaders and Academic Backbones,Shaanxi Normal University(no.18QNGG007)the Fundamental Research Funds for the Central Universities(nos.GK201902006 and GK202003036).
文摘Activatable prodrugs have received considerable attention in cancer therapy due to their high specificity and reduced side effects.However,the theranostic prodrug with multiple cancerous organelles targeting and combinational therapy is still rare.In this report,an esterase-responsive prodrug tetraphenylethylene functionalized quinolinium-ester-chlorambucil(TPEQC)was developed for dual organelles-targeted and image-guided cancer therapy through synergetic chemotherapy(CT)and photodynamic therapy(PDT).TPE-QC was constructed by conjugating an anticancer drug of chlorambucil with an aggregation-induced emission active photosensitizer of tetraphenylethylene functionalized hydroxyethyl quinolinium(TPE-QO)via the hydrolyzable ester linkage.The fluorescence and photosensitization of TPE-QC were initially quenched because of the photoinduced electron transfer(PET)effect.After reacting with esterase,the ester group of TPE-QC could be selectively hydrolyzed to release chlorambucil and TPE-QO,which terminated the PET process and switched on the fluorescence and photosensitization.Benefitting from the overexpressed esterase in cancer cells,TPE-QC could be efficiently activated in cancer cells rather than in normal cells,while the restoredfluorescence could preciselymonitor the release of TPE-QC.Importantly,activated TPE-QC accumulated in both organelles of lysosome and mitochondria,resulting in enhanced anticancer potency.In vivo experiments demonstrated that TPE-QC displayed efficient tumor microenvironment-activatable features and excellent tumor therapeutic effects through combinational CT and PDT.
文摘Net area change analysis can dramatically underestimate total change of land cover, even sometimes seriously misinterpret ecological processes of the ecosystem, especially in arid or semiarid zones. In this paper, a suite of indices are presented to characterize land-cover swaps that may seriously damage the ecosystem in arid or semiarid zones, based on swap-change areas extracted from remotely sensed images. First, swap percentage of total area and swap intensity of total changes were used to determine the status of land-cover swap change in an area. Then, dominated swap category and individual swap- change intensity for a land-cover category were used to determine flagged land-cover swap-change categories. Finally, swap-change mode and Pielou＇s index were used to determine the land-cover swap-change processes of dominant categories. A case study is conducted using this approach, based on two land-cover maps in the 1980s and 2000 in Naiman Qi, Tongliao City, Inner Mongolia, China. This study shows that the approach can clearly quantify the severity and flagged classes of land-cover swap-change and reveal their relationship with ecological processes of the ecosystem. These results indicate that the approach can give deep insights into swap change, which can be very valuable to land-cover policy making and management.
